Machine Vision Dispatch Verification via Object Label Recognition
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Solution Overview
Problem
Current methods lack a reliable system to monitor, track, and verify the physical status of items during shipment, leading to issues like chargebacks where customers dispute delivery, causing financial and logistical challenges for stakeholders.
Innovation Solution
The implementation of machine vision systems that use object and label recognition to initiate and manage video recording sessions, capturing the packaging and transport processes, providing a digital chain of custody for items through machine learning models and MV computing devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If machine vision systems with continuous video recording are implemented to track and verify item dispatch, then reliability of delivery verification is improved, but device complexity and cost increase
Solution Approach 1:
The system pre-positions machine vision devices at critical checkpoints (warehouse, distribution center, delivery location) and pre-configures automated triggering mechanisms. When an item arrives at a checkpoint, the pre-set triggers automatically initiate video recording without requiring manual activation, ensuring continuous verification while maintaining system simplicity
Solution Approach 2:
The machine vision system operates autonomously by automatically detecting items, triggering recording sessions, capturing verification data, and transmitting records to stakeholders. The system serves itself by eliminating the need for manual operation, thereby improving reliability without proportionally increasing operational complexity
2Loss of information
If machine vision systems are deployed at multiple checkpoints to provide complete chain of custody, then loss of information is reduced, but loss of time and resources increase
Solution Approach 1:
The system maintains continuous video recording at each checkpoint from the moment an item arrives until it departs or is delivered. This uninterrupted recording ensures complete chain of custody information is captured without gaps, while automated processes minimize the time stakeholders need to spend on verification
Solution Approach 2:
The system provides real-time feedback to all stakeholders (vendor, financial institution, customer) through automatic transmission of verification records. This immediate feedback loop eliminates information asymmetry and reduces the time required for dispute resolution, as all parties have access to the same verification data simultaneously
3Productivity
If automated machine vision triggering is used to start and stop video sessions based on object and label recognition, then productivity is improved, but manufacturing precision requirements increase
Solution Approach 1:
The system replaces manual verification processes with automated machine vision technology that uses optical recognition and AI algorithms to identify items and triggers. This substitution dramatically improves productivity by eliminating manual labor, while the automated systems can be trained and adjusted to achieve required recognition accuracy without increasing physical precision requirements
Data Source
AI summary
Disclosed embodiments can include a system for utilizing machine vision to verify dispatch of items. The disclosure provides a system having dispatch module comprising one or more processors and a memory storing instructions are configured to cause the dispatch module to perform a method. The method includes receiving a dispatch request for a first item. The method includes receiving, from a machine vision (MV) computing device, a first trigger of object recognition for the first item. The method includes initiating the first video comprising a process of packaging the first item. The method includes receiving a second trigger of label recognition associated with the first item. The method includes discontinuing the first video processing session. The method includes receiving a third trigger of label recognition associated with the first item. The method includes initiating a second video processing session to save a second video captured by the MV computing device.